Abstract

These talks will be presented at Diagrams 2014 and Visual Languages and Human-Centric Computing 2014.

1. Teach & Try: end-user machine learning in spreadsheets

The modern economy increasingly relies on exploratory data analysis. Much of this is dependent on data scientists – expert statisticians who process data using statistical tools and programming languages. Our goal is to offer some of this analytical power to end-users who have no statistical training through simple interaction techniques and metaphors. We describe a spreadsheet-based interaction technique that can be used to build and apply sophisticated statistical models such as neural networks, decision trees, support vector machines and linear regression. We present the results of an experiment demonstrating that our prototype can be understood and successfully applied by users having no professional training in statistics or computing, and that the experience of interacting with the system leads them to acquire some understanding of the concepts underlying exploratory statistical modelling.

2. Hunches and Sketches: interacting with big data through approximate visualisations

Information visualisation presents powerful techniques for data analytics. However, rendering visualisations of big datasets is impractical on commodity hardware. There is increasing interest in approaches where data sampling and probabilistic algorithms are used to support faster processing of large datasets. This approach to approximate computation has not yet paid close attention to the way that approximate visualisations are perceived and employed by human users, as a specific variety of diagrammatic convention. Our intent is to apply this understanding of approximate visualisations as a diagrammatic class to mainstream data science and information visualisation research.